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首页> 外文期刊>Food analytical methods >The Effect of Path Length on the Measurement Accuracies of Wine Chemical Parameters by UV, Visible, and Near-Infrared Spectroscopy
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The Effect of Path Length on the Measurement Accuracies of Wine Chemical Parameters by UV, Visible, and Near-Infrared Spectroscopy

机译:路径长度对紫外,可见和近红外光谱法测量葡萄酒参数测量精度的影响

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摘要

The use of spectral measurements using either UV, visible (VIS), or near-infrared (NIR) spectroscopy to characterize wines or to predict wine chemical composition has been extensively reported. However, little is known about the effect of path length on the UV, VIS, and NIR spectrum of wine and the subsequent effect on the performance of calibrations used to measure chemical composition. Several parameters influence the spectra of organic molecules in the NIR region, with path length and temperature being one of the most important factors affecting the intensity of the absorptions. In this study, the effect of path length on the standard error of UV, VIS, and NIR calibration models to predict phenolic compounds was evaluated. Nineteen red and 13 white wines were analyzed in the UV, VIS, and NIR regions (200-2500 nm) in transmission mode using two effective path lengths 0.1 and 1 mm. Principal component analysis (PCA) and partial least squares (PLS) regression models were developed using full cross validation (leave-one-out). These models were used to interpret the spectra and to develop calibrations for phenolic compounds. These results indicated that path length has an effect on the standard error of cross validation (SECV) absolute values obtained for the PLS calibration models used to predict phenolic compounds in both red and white wines. However, no statistically significant differences were observed (p > 0.05). The practical implication of this study was that the path length of scanning for wines has an effect on the calibration accuracies; however, they are non-statistically different. Main differences were observed in the PCA score plot. Overall, well-defined protocols need to be defined for routine use of these methods in research and by the industry.
机译:广泛地报道了使用使用UV,可见(VI),可见(VI)或近红外(NIR)光谱或预测葡萄酒化学成分的紫外线或近红外(NIR)光谱测量的使用。然而,关于葡萄酒的UV,VIS和NIR光谱的路径长度对葡萄酒谱的影响几乎没有着名,随后对用于测量化学成分的校准性能的后续影响。几个参数影响NIR区域有机分子的光谱,具有路径长度和温度是影响吸收强度的最重要因素之一。在该研究中,评价了路径长度对预测酚类化合物的UV,VIS和NIR校准模型标准误差的影响。在传输模式下,在UV,VIS和NIR区域(200-2500nm)中分析了十九个红色和13个白色葡萄酒,使用两个有效的路径长度0.1和1mm。主要成分分析(PCA)和部分最小二乘(PLS)回归模型是使用完整的交叉验证(休留On-Out)开发的。这些模型用于解释光谱并开发酚类化合物的校准。这些结果表明,路径长度对用于预测红色和白色葡萄酒中的PLS校准模型的PLS校准模型获得的交叉验证的标准误差(SECV)绝对值。但是,没有观察到统计学上显着的差异(p> 0.05)。本研究的实际含义是扫描扫描的路径长度对校准精度有影响;但是,它们是非统计学上的。在PCA分数图中观察到主要差异。总体而言,需要定义明确的协议,以便在研究和行业中常规使用这些方法。

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